Nosql Essay

In order to overcome these limitations, a new database model known as Not Only SQL (NoSQL) database emerged with a set of new features. The main objective of NoSQL is not to discard SQL, but to be used as an alternative database data model for new features [1] [2] [3]. NoSQL database increases the performance of relational databases by a set of new characteristics and advantages. In contrast to relational databases, NoSQL databases introduced an additional feature that provides flexible and horizontal scalability and taking advantage of new clusters. The rise of NoSQL provides cost-effective management of data in modern web applications. With its new features, NoSQL can be used with applications that have a large transaction, and require low-latency access to huge datasets, service availability while

For the purpose of this paper, we are going to focus on these three type of NoSQL database BigTable, Cassandra, DynamoDB.

NoSQL databases are a significant departure from the relational model that has dominated the business world for the past few decades. Standing for “Not Only SQL,” these products are all some variation of a non-relational, key-value pair database, and they are becoming very popular with companies that use Big Data and prioritize speed or availability over consistency of data.

In recent years, the distributed database system has been emerging as an important area of information processing, and its popularity is increasing rapidly. A distributed database is a database that is under the control of a central DBMS in which not all storage devices are attached to a common CPU. It may be stored on multiple computers located in the same physical location, or may be dispersed over a network of interconnected computers. Collections of data (e.g., in a database) can be distributed across multiple physical locations. In short, a distributed database is a logically interrelated collection of shared data, and a description of this data is physically distributed over a computer network. A

STRUCTURE OF DATA: The data structure of a relational database comprises of table structure. Every table is identified by a unique name or label. The data tables are described as the collection of rows and columns. Each row of the table is known as the record and each column is known as the field of the specific data table. All the data sets are well organized and logical linked to each other through definite and unique relationships. A table, therefore can also be defined as the “structured collection of relationships”. The fundamental aim of developing No SQL database systems is to easily and effectively handle vast quantities of data or information in advanced web-scale applications. In order to achieve this purpose, the No SQL systems are designed as the schema-free database systems. There are different modes to define the No SQL databases that typically depend on the requirements of the data that has to be managed. The data model for key-value store No SQL database is

NoSQL databases are databases designed to run on clusters of computers/servers, built for the ever-increasing data storage needs for websites. Devised as a way of scaling databases horizontally which is a challenge with traditional relational databases. Scaling horizontally is the ability to add more computers/servers as nodes to a database. These “clusters” work well with write-heavy systems and allow increase storage and processing power limited only by the number of connections you can have on the network. Defined as No-Schema, No-SQL data structures mean they are not limited to the original data structure. Objects and fields etc can be implemented at

NoSQL databases had made for unraveling the Big Data issue by utilizing a distributed system to bring out excellent performance in data storage and retrieval at very large-scale. At this scale, pieces of the system often fail and NoSQL is created to handle these failures (Chow, 2013) (Ron, Shulman-Peleg, & Bronshtein, 2015). Various companies have espouse different sorts of non-relational databases, ordinarily alluded to as

For the challenges we are facing be it technical or functional we find a NoSql data base as a best fit. We found out that NoSql incorporates a wide mixed bag of various database technologies and were produced in response to the rising data needs. Also when in comparison to the RDBMS present in the market NoSql provides an enriched performance and better scalability solutions. So in search of the best fit as our solution we searched out various types of NoSql database types and found out about Document databases, Graph databases, Key value stores and other similar types. Let’s explore various market players in each of the type and find the best one.

There is a lot of buzz around Big Data and the NOSQL movement these days and rightly so. The issues with data have essentially been two-fold: find cost effective ways to store ever increasing amounts of data and information, and find ways to mine this information to extract meaningful Business Intelligence.

With the expansion of the internet, there has been an exponential growth in the data being collected from various social media, searching patterns and online transactions. This rapid growth of data has become difficult to be handled by relational database, thus they have been replaced with NoSql databases. The NoSql databases are distributed databases that have the ability to store and process large volumes of data.

The modern RDBMS advancements are not capable of supporting unstructured information with ideal space necessity. The plan winds up plainly mind-boggling and is henceforth troublesome for designers. The requirement for unstructured information administration is so annoying with conventional RDBMS arrangements (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). Moreover, RDBMS turns out to be an exorbitant answer for creating light-footed web applications with direct information investigation necessities. NoSQL is developing as a proficient possibility in this situation, which connects the issues related with RDBMS innovation. The market development can credit to creative dispatches of NoSQL arrangements, and collective endeavors by NoSQL sellers and clients. The endeavors of organizations, to enhance their market offerings, are creating the request of NoSQL, as a back-end bolster (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). The emergence of agile software development is creating the demand for NoSQL (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). They offer users much more avenues to accept data in many different forms. NoSQL is adaptable as SQL but offers many more uses that can apply to many organizations.

In the initial stages of evolution of databases, relational databases systems was designed as a solution to the problems of flat file databases. A relational database stores data in multiple table. This technique helped to overcome the issues like data duplication, data noise and inconsistency which ensured that the data is entered and stored only once. Later as the data grew in size, it became a challenging task to handle such a significantly large amount of data. Key features like high data velocity, data variety, data volume and data complexity are few important reasons which the traditional database systems failed to handle successfully. As a result NoSQL came into

As there is a rise in data volumes, the manageability of data and storing these huge volumes of data became a cause of concern to most of the organizations. It was during this period when Number of SQL or more popularly NoSQL was introduced, to process these large amounts of data efficiently and effectively. For this purpose, various Data Store categories were developed, based on the different data models. Some of the categories are:

In this paper, we will review one of the graph database (Neo4j), which the graph database is part of the emerging technology that is called NoSQL and compared it with one of the traditional relational databases (MySQL). MySQL, it is being another name for Relational Databases and it has been used for a long time period until now. However, with the emergence of Big Data there was clearly a need for more flexible databases. Facebook 's Graph Search use Neo4j, a graph database, is an application which clearly displays how relationships need to be modeled in a more efficient and sophisticated manner than using conventional relational models. In this paper, we will make a comparison between MySQL and Neo4j based on the features like ACID, replication, availability and the language that is used in both of them.

Present day most of the clients are using the traditional databases like Oracle, DB2 etc and are experiencing problems in storage and performance. A large number of changes are required so that they can overcome all the drawback of the traditional database and researches are carrying out which is resulting in the database which differ from the normal database characteristics. Various number of clients are changing to NoSQL to overcome the drawbacks they are facing in traditional Database. So NoSQL have increasing demand because of following properties: